code: def data_three_groups(self):
      time = [
          88,
          62,
          81,
          64,
          19,
          35,
          49,
          82,
          57,
          6,
          97,
          52,
          4,
          90,
          16,
          92,
          4,
          59,
          90,
          71,
          39,
          94,
          68,
          77,
          67,
          15,
          67,
          7,
          32,
          14,
          39,
          26,
          24,
          2,
          4,
          95,
          2,
          12,
          94,
          64,
          68,
          16,
          99,
          6,
          57,
          81,
          53,
          33,
          31,
          91,
          91,
      ]
      status = [
          False,
          False,
          True,
          False,
          False,
          False,
          True,
          True,
          True,
          True,
          True,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          False,
          True,
          False,
          False,
          True,
          False,
          True,
          True,
          False,
          False,
          False,
          True,
          False,
          False,
          True,
          False,
          False,
          True,
          False,
          True,
          False,
          True,
          False,
          False,
          True,
          False,
          False,
      ]
      y = Surv.from_arrays(status, time)
      x = np.array(
          [
              1,
              13,
              1,
              1,
              13,
              4,
              1,
              4,
              4,
              4,
              1,
              4,
              13,
              4,
              4,
              1,
              13,
              4,
              4,
              4,
              4,
              13,
              4,
              13,
              1,
              4,
              4,
              13,
              13,
              4,
              13,
              13,
              1,
              4,
              4,
              4,
              13,
              4,
              13,
              4,
              13,
              13,
              13,
              1,
              13,
              13,
              1,
              13,
              13,
              13,
              13,
          ]
      )
  
      expected_chisq = 0.0398155305699465
      expected_pval = 0.980289085821579
      return (y, x), (expected_chisq, expected_pval)
  
imports: import numpy
  from numpy.testing import assert_almost_equal
  import pandas
  from pandas.testing import assert_frame_equal
  import pytest
  from sksurv.compare import compare_survival
  from sksurv.datasets import load_veterans_lung_cancer
  from sksurv.testing import FixtureParameterFactory
  from sksurv.util import Surv
label_desc: Use image node_id 9 for calling the LogRankToyCases obj's underlying member method code with example usage: obj.data_three_groups() and returns: y,  x,  expected_chisq,  expected_pval